Comparison
SafeWeave vs CodeQL
CodeQL is GitHub’s semantic analysis engine: it compiles your code into a queryable database so you can write precise dataflow queries to find vulnerabilities. It is powerful and is the engine behind GitHub code scanning. SafeWeave is built for a different moment — fast, broad, local feedback inside the AI editor. Here is a fair architectural comparison.
Side by side
| Dimension | SafeWeave | CodeQL |
|---|---|---|
| AI-editor / MCP-native | MCP-native; scans run from inside AI editors as part of the coding loop. | An analysis engine queried via CLI or run through GitHub code scanning; not an MCP-based editor workflow. |
| Local execution / code privacy | Runs locally; source stays on your machine for a scan. | The CLI can build and analyze databases locally; it is also commonly run within GitHub code scanning. |
| Install effort | One MCP server in your editor config; scan immediately. | Set up the CodeQL CLI, build a database for the language, and run queries — more involved, especially for compiled languages. |
| Scan model | 8 scanners in a ~12s pass with 300+ bundled rules, tuned for fast feedback while coding. | Deep semantic, query-based dataflow analysis — thorough and precise, and typically heavier per run. |
| Pricing posture / entry price | Open-core (MIT core): $0 Free, $15 Developer Pro, $29 Cloud, $99 Team. | Free for open-source/research use; commercial use generally comes via a GitHub Advanced Security license. |
| Best-fit use case | Developers wanting broad, fast coverage across many scan types in the editor. | Security researchers and engineers writing precise custom queries to hunt deep dataflow vulnerabilities. |
CodeQL: GitHub's semantic code analysis engine that treats code as data you query for deep dataflow vulnerabilities. Comparisons are qualitative and architectural — capabilities and pricing change, so verify the latest details on each vendor’s site.
When to choose which
Choose SafeWeave when…
Choose SafeWeave when you want broad coverage and fast, local feedback across many security domains while you code, without building analysis databases.
Choose CodeQL when…
Choose CodeQL when you need deep, customizable semantic analysis and are willing to invest in writing queries to find subtle, dataflow-heavy vulnerabilities.
FAQ
Is SafeWeave as deep as CodeQL for finding vulnerabilities?
They optimize for different goals. CodeQL's query-based semantic analysis is exceptional for deep, custom dataflow hunting. SafeWeave optimizes for fast, broad, local coverage across eight scan types inside the editor. For the deepest custom dataflow analysis, CodeQL is purpose-built.
Does SafeWeave require building a database like CodeQL?
No. SafeWeave runs scans directly and returns results in roughly twelve seconds, with no separate database-build step.
Can I use both?
Yes. Many teams use SafeWeave locally for fast feedback during development and run CodeQL (often via GitHub code scanning) for deeper analysis on commits and pull requests.
See SafeWeave in your editor
Eight scanners, ~12 seconds, running locally and MCP-native. Free forever to start — no credit card required.